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st: Re: Predicting Random Effects from a Crossed-Level Model using xtmelogit


From   "Joseph Coveney" <jcoveney@bigplanet.com>
To   <statalist@hsphsun2.harvard.edu>
Subject   st: Re: Predicting Random Effects from a Crossed-Level Model using xtmelogit
Date   Tue, 29 Dec 2009 15:13:58 +0900

Albert Lee wrote:

This may be obvious.  If so, I apologize in advance.

I'm estimating a logistic model with crossed-level random effects.  The outcome
binary variable is fail with one fixed-effect independent binary variable
refinance.  The three crossed-level random effects are VAR1, VAR2 and VAR3.  The
STATA command I used is as below:

xtmelogit fail refinance || _all:R.VAR1 || _all:R.VAR2 || _all:R.VAR3 

After estimating this model, I tried to recover the random effects of VAR3
using:

predict u, reffects level(VAR3)

However, u only contains missing values.

I would very much appreciate if someone can help me recovering these predicted
random effects.

--------------------------------------------------------------------------------

Doesn't -xtmelogit- use Laplace approximation by default when fitting a
cross-classified model?  I believe that you would need to specify at least
three, or so, integration points (abscissa weights) in order to get empirical
Bayes predictions of individual random effects.

Joseph Coveney



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